Creditworthiness of individuals and businesses has long been a quantifiable measure from which many personal and commercial transactions are based. The creditworthiness of an individual is used to determine terms (e.g., amounts and interest rates) when individuals seek home mortgage loans, personal loans, property rental, and credit cards. Several credit agencies exist and operate to determine an individual's creditworthiness and to sell that information to interested buyers. Credit agencies derive the creditworthiness of individuals by monitoring individual spending habits, payment habits, net worth, etc. Credit agencies convert these and other monitored behaviors into a quantifiable credit score that has been standardized to range between 300-850 points, with a higher score representing greater creditworthiness and a lower score representing lesser creditworthiness.
Business creditworthiness is also a quantifiable measure that drives many business transactions. However, deriving business creditworthiness is a fundamentally more complex problem than deriving an individual's creditworthiness. For individuals, there is a one-to-one correspondence between an identifier (i.e., social security number) and the individual. Such is not the case for many businesses. A business may operate under different names, subsidiaries, branches, and franchises as some examples. Moreover, tracking business assets, accounts, and transactions is further complicated because businesses merge, go out of business, start anew, split, etc. Accordingly, more resources are needed to monitor and analyze business creditworthiness. Companies, such as Dun & Bradstreet®, operate to monitor and derive the creditworthiness of businesses. Business credit reports can be purchased from Dun & Bradstreet and other such business credit reporting companies. Sales of such information have become a multi-billion dollar industry.
While critical to some small business needs, business creditworthiness is often immaterial to determining the day-to-day success of the small business. For instance, whether a client leaves satisfied with a service or a product that has been purchased from the small business is instrumental in determining whether that client will be a repeat customer or will provide referrals to encourage others to visit the small business. A sufficient number of good client experiences beneficially increases the exposure of the small business, thereby resulting in better chances of growth, success, and profitability. Conversely, a sufficient number of bad client experiences can doom a small business. The success of the small business is therefore predicated more on generated goodwill, reputation, satisfaction, and other such criteria that impact the small business operations on a day-to-day basis than it is on business creditworthiness. Goodwill, reputation, satisfaction, and other such criteria that impact the small business operations on a day-to-day basis are hereinafter referred to as credibility.
Ascertaining the credibility for any entity whether an individual or business is complicated by virtue of the varied and distributed nature of credibility data. Credibility data exists in various forms including qualitative credibility data and quantitative credibility data. Qualitative data includes customer and professional review data, blog content, and social media content as some examples. Some data sources from which qualitative data about various entities may be acquired are internet websites such as www.yelp.com, www.citysearch.com, www.zagat.com, www.gayot.com, www.facebook.com, and www.twitter.com. Quantitative data includes different measures of an entity's credibility as quantified to a scale, ranking, or rating. Consequently, credibility data is neither standardized nor normalized and each data source provides an independent and disjoint view of the credibility for an entity. Other factors also affecting the credibility of a particular individual or business entity include the presence and visibility of the entity and the partnerships and relationships established by the entity as some examples.
It is very time consuming, inaccurate, and difficult for the small business or other entity to piece together its credibility from these varied data sources. Specifically, the small business does not have the tools or the resources to continually scour the different credibility data sources to aggregate sufficient credibility data from which to derive its credibility. Further exacerbating the problem is that even when the credibility data is properly aggregated, making sense of that credibility data to arrive at an overall view of the business credibility is complicated by the amount of credibility data and the non-standard, non-uniform, and qualitative nature of the credibility data.
Accordingly, there is a need to provide various visualization tools that provide a holistic and comprehensive view of the creditability of an entity. Moreover, entities want to understand the different dimensions of credibility from which their overall credibility is derived. Each credibility dimension provides insight into what parts of the entity are helping its credibility and what parts are detrimentally affecting its credibility. Accordingly, there is further a need for the visualization tools to provide a meaningful, concise, interactive, and easily navigable interface from which to understand the derivation of an entity's credibility based on its various dimensions.